Plant Disease Detection Using Image Processing and Machine Learning

TL;DR

This paper presents a machine learning-based image processing system that efficiently detects 20 crop diseases across 5 plants with high accuracy, aiming to assist agricultural disease diagnosis.

Contribution

It introduces a novel computer vision and machine learning approach capable of identifying multiple crop diseases with high accuracy, reducing manual effort.

Findings

Detects 20 diseases with 93% accuracy

Applicable to 5 common plants

Uses computer vision and machine learning

Abstract

One of the important and tedious task in agricultural practices is the detection of the disease on crops. It requires huge time as well as skilled labor. This paper proposes a smart and efficient technique for detection of crop disease which uses computer vision and machine learning techniques. The proposed system is able to detect 20 different diseases of 5 common plants with 93% accuracy.